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Interpreting TSLS Estimators in Information Provision Experiments

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Research uncovers the impact of passive control designs on TSLS estimators, highlighting key conditions influencing causal effect estimates.

TSLS estimators can recover a positive-weighted average of causal effects when proper conditions are met.
Common passive control estimators may produce negative weights, impacting estimate validity and significance.
This assessment draws on both simulations and empirical applications to illustrate estimator effects.
Practical recommendations are provided to overcome estimation challenges in information provision experiments.

Vilfort et al. (2025) studied this question.

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Research uncovers the impact of passive control designs on TSLS estimators, highlighting key conditions influencing causal effect estimates.